The present invention relates to the cancellation of noise or vibration signals using a plurality of reference sensors, actuators, and/or error sensors; a method termed multi-channel control, and to a control computer or controller capable of performing the functions required to accomplish such control. It relates in particular to both (1) the multi-channel active control of noise or vibration, and (2) the multi-channel separation of a signal from a noisy environment.
Multi-channel active control of unwanted noise or vibration signals is applicable to a variety of circumstances in which noise and vibration occur. Three examples are: the active control of noise in interior spaces such as aircraft or automobiles; the active control of low level low frequency vibration in high precision manufacturing machinery such as that used in the semiconductor industry; and the mitigation of traffic noise in residential areas near major highways.
Multi-channel signal separation of unwanted noise or vibration signals, on the other hand, is applicable to a different set of circumstances. Examples of applications are the removal of own-vehicle noise from detection microphones mounted exterior to a military vehicle (i.e., a HumVee); the removal of unwanted signals from measurements by scientific or medical instruments such as the removal of muscle artifact from electro-encephalograms performed on patients while relevant muscles are active as during an epileptic seizure; and the removal of several kinds of interference in telecommunications.
In the case of active control, it is known in the art that unwanted noise or vibration present in a physical environment can be mitigated by generating signals or vibrations to counter the unwanted noise or vibrations. In the case of so-called feed-forward active control, it is known in the art that noise or vibration reference sensors can be advantageously used to characterize the noise or vibration to be removed from the physical environment by applying loudspeakers or other actuators to cancel the offending noise or vibration.
In the case of signal separation, it is known in the art that unwanted noise appearing in a measurement can be removed from that measurement by the use of noise reference sensors. Such sensors are capable of characterizing the noise appearing in the primary (signal) sensor, thereby allowing the subtraction of that noise from the signal out of the primary sensor to obtain a corrected low-noise output.
In both active control and signal separation, it has been recognized that it is sometimes advantageous to use multi-channel control, generally involving the use of more than a single reference sensor, when there is more than a single independent source of noise to be canceled. However, it has also been recognized in the prior art that there is a limit on the number of reference sensors that can be used effectively. It has been a problem in the art that there is no known method for ascertaining the precise number and optimal locations of reference sensors required to provide effective cancellation of the noise appearing in either the physical environment (active control) or the signal from a primary sensor (signal separation). Furthermore in the case of signal separation, under most circumstances it is not possible to obtain a reference sensor reading which is totally free of the primary signal, which as a result can lead to cancellation of the primary signal itself when "too many" reference sensors are used.
Consequently, a primary problem with approaches to the multi-channel control of noise or vibration (either active or signal separation) is the inevitable presence of redundant information in the noise or vibration reference measurements. This problem is described below in greater detail for the particular case of active control. The problem as well as its solution are essentially the same for the case of signal separation.
In general, active noise control uses adaptive filtering to drive loudspeaker "actuators" to cancel existing noise or vibration, by producing antinoise or vibration. Adaptive filtering is a long-known (since the 1940's) way of filtering that uses the statistical properties of signals. It can separate signals, even when they are in the same frequency band. If such signals are statistically independent, they can in principle be separated perfectly.
As is well known in the prior art, Norbert Wiener derived the simple matrix equation that must be solved to obtain filter coefficients for active control. Optimal filter values are derived by solving this matrix equation or inverting the matrix. However, inverting even modest size matrices in real time is a computation intensive task. In the 1960's Bernard Widrow partially solved this problem by inventing the now famous LMS algorithm, which, by an ingenious gradient approach that iteratively or recursively computes the filter coefficients, eliminates the need for inverting matrices. Since the creation of the LMS algorithm, numerous other algorithms, including the Filtered-X and others, have been superimposed on the original LMS algorithm to solve such problems as updating system transfer functions.
The LMS algorithm is simple and computationally efficient. So much so, in fact, that the LMS algorithm has been over-used or even misused. In particular, the Wiener Filter equation, which the LMS algorithm as presently used and other algorithms derived from it attempt to solve, sometimes (and in practice often) does not have a solution. As is well known, two simultaneous equations (a matrix equation) in which one equation is simply a multiple of the other cannot be solved. Unfortunately, this is what happens analogously whenever two noise reference sensors pick up the same noise source. The LMS algorithm and its derivatives must and will fail when the underlying Wiener Filter equation does not have a solution because of singularity or ill-condition.
The concepts of active noise control, feedforward control, the LMS algorithm, the Filtered-X algorithm, Wiener Filters and others, as mentioned above and as will be used hereinafter, are consistent with those as explained in texts such as Active Control of Vibration, Academic Press Limited, London, England (1996) to C. R. Fuller et al.; Active Noise Control Systems: Algorithms and DSP Implementations, John Wiley & Sons, Incorporated, New York, N.Y. (1996) to S. M. Kuo et al.; and Adaptive Signal Processing, Prentice-Hall Incorporated, Englewood Cliffs, N.J. (1985) to B. Widrow et al., all of which are hereby incorporated by reference.